{"id":"W4366747489","doi":"10.1145/3593294","title":"Data Provenance in Security and Privacy","year":2023,"lang":"en","type":"review","venue":"ACM Computing Surveys","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick; University of Saskatchewan","funders":"Mitacs","keywords":"Provenance; Computer science; Metadata; Context (archaeology); Variety (cybernetics); Data science; Internet privacy; Computer security; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01209889,0.000757713,0.001265783,0.00413711,0.001917882,0.005894765,0.001669627,0.004443241,0.005087021],"category_scores_gemma":[0.02792087,0.0005478136,0.001212692,0.006272024,0.008397684,0.01262743,0.003398172,0.004842318,0.001844824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004683169,"about_ca_system_score_gemma":0.009019943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003486165,"about_ca_topic_score_gemma":0.002613846,"domain_scores_codex":[0.9889435,0.005114642,0.0008324101,0.0009955488,0.003694333,0.0004195362],"domain_scores_gemma":[0.9687903,0.02219481,0.001544352,0.002805328,0.004133016,0.0005322733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000347237,0.00003167614,0.0005505921,0.003855817,0.000059807,0.0001703847,0.0006099593,0.001291254,0.0002441767,0.6301008,0.02429961,0.3387512],"study_design_scores_gemma":[0.00001202811,0.00003501337,0.0004842517,0.004807837,0.00003972793,0.0006336808,0.0003810824,0.0006342643,0.0003678436,0.255632,0.7369385,0.00003385566],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001136845,0.8985312,0.03744124,0.02869342,0.002928921,0.000146543,0.0002199415,0.0001140594,0.03078793],"genre_scores_gemma":[0.03566295,0.9272242,0.02037846,0.006230873,0.004276286,0.0002188178,0.0003059038,0.00006660214,0.00563592],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01209889,"threshold_uncertainty_score":0.06398582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6060179517797337,"score_gpt":0.5269220062819636,"score_spread":0.0790959454977701,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}